Triple
T32205441
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Board of Obstetrics and Gynecology |
E822655
|
entity |
| Predicate | subspecialtyCertificationIn |
P60165
|
FINISHED |
| Object | maternal-fetal medicine |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: maternal-fetal medicine | Statement: [American Board of Obstetrics and Gynecology, subspecialtyCertificationIn, maternal-fetal medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subspecialtyCertificationIn Context triple: [American Board of Obstetrics and Gynecology, subspecialtyCertificationIn, maternal-fetal medicine]
-
A.
isConsideredSpecialtyOf
Indicates that one field, practice, or area of expertise is regarded as a specialized branch or subset of another broader field.
-
B.
subjectSpecialization
Indicates that one subject focuses on, or has expertise in, a particular field, topic, or area of knowledge.
-
C.
hasSpecialty
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
D.
subDisciplineOf
Indicates that one discipline is a more specialized or narrower field within another, broader discipline.
-
E.
typeOfCertification
chosen
Indicates the specific kind or category of certification associated with an entity.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f349093174819086e633c190a51aa8 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6bb840e288190b6b188b7f6928601 |
completed | May 3, 2026, 3:05 a.m. |
| PD | Predicate disambiguation | batch_69f6b3aa892481908d29283a074e6722 |
completed | May 3, 2026, 2:32 a.m. |
Created at: May 1, 2026, 12:36 a.m.